SMAA: Enhanced Subpixel Morphological Antialiasing

We present a new image-based, post-processing antialiasing technique, that offers practical solutions to all the common problems of existing filter-based antialiasing algorithms. It yields better pattern detection to handle sharp geometric features and diagonal shapes. Our edge detection scheme exploits local contrast features, along with accelerated and more precise distance searches, which allows to better recognize the patterns to antialias. Our method is capable of reconstructing subpixel features, comparable to 4x multisampling, and is fully customizable, so that every feature can be turned on or off, adjusting to particular needs. We propose four different presets, from the basic level to adding spatial multisampling and temporal supersampling. Even this full-fledged version achieves performances that are on-par with the fastest approaches available, while yielding superior quality.